This paper explores the unsourced/uncoordinated random access (URA) problem for integrated sensing and communication (ISAC) systems. Recent findings indicate that conventional multiple access strategies, such as treating interference as noise (TIN) and time-division multiple access (TDMA), are often overwhelmed and fail to support the rapidly increasing number of active users. To address this, the unsourced ISAC (UNISAC) system model has emerged as a promising framework for future ISAC networks. In this work, we adopt a realistic channel model and propose the use of a fluid antenna system (FAS) for UNISAC. We derive the achievable performance bounds and floor for the proposed FAS-UNISAC to demonstrate its significant potential. For communication, the randomized overlapping of channel responses from different scattering paths yields substantial gains within a compact antenna space.We prove that the joint detection and decoding error is inversely proportional to the channel gain. For line-of-sight (LOS) only channel model, leveraging covariance information through the spatial diversity of FAS effectively expands the receiving aperture, thereby enhancing sensing resolution. A universal sensing upper bound is established as a benchmark for potential sensing methods. Additionally, we investigate the benefits of asynchronous transmission, which introduces an extra degree of freedom through resource multiplexing gains via randomized timing offsets among users. Our results show that the spatial diversity inherent in FAS significantly enhances the supported user volume, as well as the sensing and communication capabilities.

In this paper, we introduce a novel framework for multiple access code design under the finite blocklength regime in multi-input and multi-output (MIMO) systems, termed coded pattern multiple access (CPMA). CPMA involves a series of multiple access code designs facilitated by a sparse pattern mapper/demapper, enabling independent information projection onto transmission patterns. Unlike existing approaches, the mapping and demapping of patterns are completely isolated components, ensuring energy-efficient transmission. In this work, we establish and analyze practical CPMA models, thoroughly investigating the performance limits of a potential non-bijective demapper. Closed-form and integral-form solutions are provided to describe these performance limits. Additionally, we present a practical application of CPMA: the coded pattern unsourced random access (CPURA) scheme. This scheme is designed for finite blocklength transmission under a quasi-static fading channel. The proposed CPURA achieves bound-approaching performance for large user groups, outperforming existing state-of-the-art methods in the context of massive machine-type communications (mMTC). Notably, the minimum required energy-per-bit to support 1,200 active users exhibits only a 1.3 dB gap from the achievable bound, validating the potential of the proposed CPMA framework.

In this work, the unsourced random access problem over a quasi-static fading channel is discussed with a massive number of antennas at the receiver. A novel transmission protocol called the Less-Is-More (LIM) strategy is proposed. Only a small portion of the data needs to be encoded and transmitted into the channel, while the remaining data bits are embedded into the patterns of sparse frames and implicitly transmitted without requiring power assumptions. Specifically, LIM divides the entire blocklength into several chunks and split the transmission in each chunk into two phases: one for pilot signals and the other for sparsely scattered modulated constellation symbols. Each user selects a single chunk to send its frame into the channel, and the frame consists of multiple scattering patterns determined by a large portion of the message bits. Consequently, the proposed scheme can implement strong channel coding with a relatively long code length, sparse frames with tolerable multi-user interference, and a high level of constellation power. Furthermore, we analyze the performance of the proposed scheme using normal approximations and provide a detailed complexity analysis of the major decoder component. Numerical results indicate that the proposed scheme performs competitively compared to state-of-the-art methods, achieving near-theoretical bound performance.

This paper investigates fluid antenna systems (FASs) subject to finite-blocklength (FBL) constraints, motivated by the strict reliability-latency and ultra-massive connectivity requirements of future wireless networks. While FAS performance has been widely studied in the asymptotic regime, its behavior under FBL remains largely unexplored. Our objective is to develop a unified set of analytical tools for evaluating FASs under FBL that remains applicable across different spatial-correlation models. First, to establish accurate benchmarks for non-orthogonal finite-length user signature design, we characterize both the average and the worst-case correlation coefficients via extreme value theory (EVT) and derive closed-form predictions of the achievable correlation levels. Second, taking block error rate (BLER) as the fundamental FBL metric, we study joint detection and decoding in FAS-assisted links and derive a closed-form BLER expression that is universally applicable across channel models. Additionally, we revisit outage probability (OP) in the FBL regime and obtain tractable OP characterizations for both FASs and conventional multiple fixed-position antenna (FPA) systems. In order to reduce the computational burden for multi-fold integrals in correlated fading models, we further propose a Taylor-expansion-assisted mean value theorem for integrals (MVTI), thus enabling efficient performance evaluation with marginal accuracy loss. Numerical results validate the analysis and reveal that even single-antenna FASs can have superior spatial diversity relative to conventional multi-FPA systems. Moreover, under both FBL and interference-limited environments, FASs provide improved energy, spectral, and hardware efficiencies, hence highlighting FAS as a promising enabler for next-generation wireless networks.

In this work, we discuss the problem of unsourced random access (URA) over a Gaussian multiple access channel (GMAC). To address the challenges posed by emerging massive machine-type connectivity, URA reframes multiple access as a coding-theoretic problem. The sparse code-oriented schemes are highly valued because they are widely used in existing protocols, making their implementation require only minimal changes to current networks. However, drawbacks such as the heavy reliance on extrinsic feedback from powerful channel codes and the lack of transmission robustness pose obstacles to the development of sparse codes. To address these drawbacks, a novel sparse code structure based on a universally applicable power division strategy is proposed. Comprehensive numerical results validate the effectiveness of the proposed scheme. Specifically, by employing the proposed power division method, which is derived analytically and does not require extensive simulations, a performance improvement of approximately 2.8 dB is achieved compared to schemes with identical channel code setups.

This paper addresses the unsourced/uncoordinated random access problem in an integrated sensing and communications (ISAC) system, with a focus on uplink multiple access code design. Recent theoretical advancements highlight that an ISAC system will be overwhelmed by the increasing number of active devices, driven by the growth of massive machine-type communication (mMTC). To meet the demands of future mMTC network, fundamental solutions are required that ensure robust capacity while maintaining favorable energy and spectral efficiency. One promising approach to support emerging massive connectivity is the development of systems based on the unsourced ISAC (UNISAC) framework. This paper proposes a spectrum-sharing compressive sensing-based UNISAC (SSCS-UNISAC) and offers insights into the practical design of UNISAC multiple access codes. In this framework, both communication signals (data transmission) and sensing signals (e.g., radar echoes) overlap within finite channel uses and are transmitted via the proposed UNISAC protocol. The proposed decoder exhibits robust performance, providing 20-30 dB capacity gains compared to conventional protocols such as TDMA and ALOHA. Numerical results validate the promising performance of the proposed scheme.

This work explores the channel estimation (CE) problem in uplink transmission for unsourced random access (URA) with a fluid antenna receiver. The additional spatial diversity in a fluid antenna system (FAS) addresses the needs of URA design in multiple-input and multiple-output (MIMO) systems. We present two CE strategies based on the activation of different FAS ports, namely alternate ports and partial ports CE. Both strategies facilitate the estimation of channel coefficients and angles of arrival (AoAs). Additionally, we discuss how to refine channel estimation by leveraging the sparsity of finite scatterers. Specifically, the proposed partial ports CE strategy is implemented using a regularized estimator, and we optimize the estimator's parameter to achieve the desired AoA precision and refinement. Extensive numerical results demonstrate the feasibility of the proposed strategies, and a comparison with a conventional receiver using half-wavelength antennas highlights the promising future of integrating URA and FAS.

This paper discusses the unsourced random access (URA) problem in quasi-static fading multi-input and multi-output (MIMO) channel. A novel less-is-more (LIM) strategy is firstly proposed where only a small portion of data with strong energy-per-unit is transmitted into channels while others are implicitly embedded into the transmission. The LIM encoder generates extreme transmission sparsity and strong denoising capability. Correspondingly, the proposed decoder is elaborated with complexity analyses. Numerical results demonstrate that the proposed LIM-URA design shows a capacity performance close to the recently established MIMO achievable bound compared with other state-of-the-arts under identical spectral efficiency.

This article studies the topic of probabilistic on-off division multiple access (ODMA) system design under multiple input-multiple output (MIMO) and massive MIMO with hybrid analog/digital architectures for unsourced random access (URA). Though probabilistic ODMA in Gaussian multiple access channel (GMAC) manifests desirable capacity, probabilistic ODMA extension towards MIMO and hybrid massive MIMO encounters problems have not been discussed. Specifically, a portion of data bits are utilized to select on-off patterns and not transmitted. These pattern-correlated bits and others are restored iteratively with pilot-free transmission in the so-called process of joint pattern and data detection. Discrepant to the state-of-arts, such as interleaving division multiple access (IDMA), where prior of patterns is an essential prerequest for the later detection, probabilistic ODMA detects pattern and data simultaneously with only linearly modulated signals. In this work, two probabilistic ODMA transceiver designs are proposed by different ranks of signal component matrix in MIMO and hybrid massive MIMO. Overall, our proposed designs retain the simplicity of the original ODMA and further exploits the sparsity of on-off patterns. For MIMO, on-off patterns are correlated with common codebook and a receiver is designed in the spirit of uncoupled URA. For hybrid massive MIMO, a novel probabilistic ODMA transceiver achieves probabilistic channel estimation via low-rank matrix completion aided by the sparsity of on-off patterns. Meanwhile, joint pattern and data detection is accomplished by iterative treating interference as noise (TIN) strategy. Extensive simulations are conducted under fair comparisons with state-of-the-arts to verify the validity of the proposed schemes.

The robustness of filter bank multi-carrier (FBMC) against delays is appealing for asynchronous grant-free massive connectivity systems. In this paper, we study the joint activity detection, delay and channel estimation (JADDCE) problem for filter bank multi-carrier (FBMC)-based uplink massive connectivity with asynchronous transmission and frequency-selective fading (FSF) channels. We formulate JADDCE as a compressed sensing (CS) problem to fully exploit the sparsity structure and propose an efficient algorithm based on generalized approximate message passing (GAMP) to solve it. Besides, since parameters such as noise variance and activity probability may not be perfectly known by the receiver, we introduce the expectation maximization (EM) method into the algorithm and derive the updating rules of the unknown parameters. We also utilize the analysis framework based on average mutual information (AMI) to find theoretical upper-bound of the channel estimation performance. Simulation results show satisfying detection and estimation performance of the proposed algorithm under FSF channels. Besides, the channel estimation performance can approach the theoretical upper-bound.

This work studies the unsourced random access (URA) problem via random dictionary learning over Rayleigh block-fading channels with multiple receive antennas. We propose a novel pilot-free URA equipped with a concatenated URA coding structure enabled by on-off patterns. The inherent collision problem in URA is mitigated with slotted encoding structure. Other problems of state-of-the-arts such as low code rate and inefficient transmission are well-tackled. Distinctively, activity detection is not only accomplished in the original pilot-free manner but also enhanced with softer verdict. Facing the potential false alarm (FA) error, a joint channel pruning and dictionary learning procedure maintains FA under a low level. The learning process updates the noise variance of pseudo noise with explicit models to obtain channel estimation. Subsequently, for the first time, this work realizes joint on-off pattern detection and data restoration for on-off division multiple access (ODMA) under multiple-input and multiple-output (MIMO). Also, a successive interference cancellation (SIC) structure is adopted as an iterative approach to produce desirable performance. Moreover, we analyze the approximation of error ceiling and the performance lower-bound determined by feasible deterministic parameters. Finally, numerical simulations with fair comparisons validate the viability of the proposed URA scheme.

Massive machine-type communications (mMTC) or massive access is a critical scenario in the fifth generation (5G) and the future cellular network. With the surging density of devices from millions to billions, unique pilot allocation becomes inapplicable in the user ID-incorporated grant-free random access protocol. Unsourced random access (URA) manifests itself by focusing only on unwrapping the received signals via a common codebook. In this paper, we propose a URA protocol for a massive access cellular system with multi-user single input multiple output (MIMO). The proposed scheme encompasses a codebook enabling construction of sparse transmission frame, a receiver equipped with dictionary learning and error-correcting codes and a collision resolution strategy for the collided codeword. Discrepant to the existing schemes with necessary overhead for preamble signals, no overhead or pre-defined pilot sequences are needed in the proposed scheme, which is favorable for energy-efficient transmission and latency reduction. Numerical results verify the viability of the proposed scheme in practical massive access scenario.

In this paper, a novel random scattering transceiver design for unsourced random access (URA) is investigated. Distinctive from the state-of-the-art such as coded compressed sensing (CCS) kind and interleaving division multiple access (IDMA) kind, the data is split into two portions and the back-and-forth interleaving/de-interleaving for soft information update is dismantled. A portion of the data is encoded by compressed sensing (CS) and the rest is encoded by convolutional code LDPC (CC-LDPC). Based on the principle of probabilistic data association (PDA), a receiver with a turbo PDA multi-user detector (MUD) is designed by the random scattering transmission. Meanwhile, the proposed turbo PDA detector can also cooperate with the CC-LDPC decoder. A sliding window decoding structure is embedded in the proposed receiver. Moreover, given that permeable collision in URA can undermine the system performance, this paper treats collision as interference and elaborates different slot-wise MUD signal models combining the feature of random scattering, based on which a collision resolution procedure is proposed. Empirically, the proposed scheme shows faster system performance convergence and more accurate MUD performance than the IDMA kind. Numerical results with fair comparisons validate the viability of the proposed scheme.